Manager - Data Science - Generative Artificial Intelligence - IIT/IIM/NIT/BITS/ISB/XLRI

Manager - Data Science ( Generative AI) -IIT/IIM/NIT/BITS/ISB/XLRI

Key Responsibilities & Skillsets:

- Develop and implement state-of-the-art AI models using machine learning and deep learning techniques.

- Work with large datasets to extract insights, build predictive models, and optimize AI algorithms.

- Collaborate with cross-functional teams to define and solve business problems using AI and data science.

- Develop GenAI solutions for NLP involving LLM (Large Language Models) such as GPT, Flacon, and LLaMA among others, or for Computer Vision involving GANs, Diffusion models etc.

- Create and deploy end-to-end model pipeline in cloud infrastructure such as AWS, Azure, and GCP.

- Implement customized NLP techniques to understand and process unstructured text data.

- Utilize Computer Vision methodologies to analyze and extract information from images or videos.

- Research and stay up to date with the latest advancements in AI, NLP, and Computer Vision to apply innovative solutions.

- Communicate findings and results to non-technical stakeholders and provide actionable insights.

- Optimize and fine-tune AI models to improve their performance and accuracy.

- Ensure data privacy and security practices are upheld throughout the AI development process.

Candidate Profile:

- A Master's or Ph.D. in a related field, such as Computer Science, Data Science, or a similar discipline.

- Strong experience in data science, machine learning, and AI model deployment.

- Proficiency in languages such as Python, SQL, PySpark and relevant libraries.

- Solid understanding of Gen AI models around NLP or Computer Vision and their applications.

- Excellent problem-solving skills and the ability to work on complex AI projects.

- Strong communication skills to convey technical concepts to non-technical team members.

- Experience with deep learning frameworks and tools (e.g., TensorFlow, PyTorch, LangChain).

- Knowledge of data preprocessing, feature engineering, and model evaluation.

- Familiarity with cloud platforms and big data technologies is a plus.